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Data Science is a broad interdisciplinary field that lies at the intersection of statistics, machine learning, computer science, and a wide range of application domains. The goal of Data Science is to develop methods and algorithms that can extract knowledge and insights from (huge amounts of) structured and unstructured data.
The Data Science program at TeIAS offers strong preparation in statistical modeling, optimization, machine learning, and efficient algorithm design for management and analysis of massive data.
The program benefits from full-time faculty members who are leading researchers in the areas of microeconomic theory, labor, development, education, macroeconomics, theoretical and empirical finance, banking etc..
In addition to having tuition fees waived, students will receive a monthly financial support to be able to pursue research without the need to resort to extra activities outside university. Extra research assistant positions are also available.
Full financial support will be provided for students to present their research outputs in reputable international conferences.
Students will be supervised by our faculty researchers who are active in various areas, opening room for a wide range of attractive research problems.
Current research in economics is involved with working with big data and time consuming simulations and estimations. Our unique GPU servers provide the necessary means for carrying out such large-scale data processing and deep learning experiments.
There is a growing demand for Economists and researchers. Upon graduation, students will have the opportunity to pursue a career in academia or industry.
PhD from Sapienza University
PhD from Sharif University of…
PhD from University of…
PhD from University of…
First Author of ETAPS 2023 paper
https://research.tue.nl/en/publications/compositional-learning-for-interleaving-parallel-automata
Co-author of FormaliSE 2023 paper
First author of an EMNLP 2023 (findings) paper
https://paperswithcode.com/paper/difair-a-benchmark-for-disentangled
Co-author of an EMNLP 2023 (findings) paper
Using Iran’s unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietary information on more than 53,000 farmers, we find that farmers with a stronger relationship with their branch - particularly younger and females - are more likely to receive a recovery loan. Our findings underscore that despite recent technological advancements, relationship-based branch banking is still important for agrarian societies during catastrophic events.
Keywords: Bank branch, Relationship lending, Climate change, Agricultural loans
JEL Classification: G21, G28, O13, Q14, Q54
What is the role played by marketplace lending after natural disasters? Analyzing a sample of more than one and a half million observations from Lending Club around the 33 worst natural disasters that occurred between 2013 and 2017, we find that there is an increase in the demand for marketplace loans by almost 10%. Yet, the platform does not restrict lending to individuals in the affected areas, nor do we observe an increase in interest rates. Interestingly, the performance of borrowers who receive loans after a natural disaster is not significantly different from the borrowers during normal times, indicating that the platform is competent at efficiently meeting the extra loan demand.
Keywords: Marketplace Lending, FinTech, Natural Disasters, Access to Finance, Credit Risk Assessment
JEL Classification: D14, E51, G2, Q54
This paper primarily studies the pricing of insolvent banks that are sold under the purchase and assumption resolution method of the Federal Deposit Insurance Corporation (FDIC). We analyze 586 acquisitions of solvent and insolvent U.S. banks between 2009:Q1 and 2016:Q3 and find that acquirers pay higher prices for insolvent banks with more branches or with a national charter. Our findings hence suggest that the franchise value is not only embedded in failed banks’ core deposits but also in the size of their branch networks. Moreover, bidders with more capital tend to pay lower prices for failed banks. Failed banks are sold at higher prices in more competitive auctions.
Keywords: Bank failures, Resolution, FDIC
JEL Classification: G21, G28
Using Iran’s unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietary information on more than 53,000 farmers, we find that farmers with a stronger relationship with their branch - particularly younger and females - are more likely to receive a recovery loan. Our findings underscore that despite recent technological advancements, relationship-based branch banking is still important for agrarian societies during catastrophic events.
Keywords: Bank branch, Relationship lending, Climate change, Agricultural loans
JEL Classification: G21, G28, O13, Q14, Q54
What is the role played by marketplace lending after natural disasters? Analyzing a sample of more than one and a half million observations from Lending Club around the 33 worst natural disasters that occurred between 2013 and 2017, we find that there is an increase in the demand for marketplace loans by almost 10%. Yet, the platform does not restrict lending to individuals in the affected areas, nor do we observe an increase in interest rates. Interestingly, the performance of borrowers who receive loans after a natural disaster is not significantly different from the borrowers during normal times, indicating that the platform is competent at efficiently meeting the extra loan demand.
Keywords: Marketplace Lending, FinTech, Natural Disasters, Access to Finance, Credit Risk Assessment
JEL Classification: D14, E51, G2, Q54
This paper primarily studies the pricing of insolvent banks that are sold under the purchase and assumption resolution method of the Federal Deposit Insurance Corporation (FDIC). We analyze 586 acquisitions of solvent and insolvent U.S. banks between 2009:Q1 and 2016:Q3 and find that acquirers pay higher prices for insolvent banks with more branches or with a national charter. Our findings hence suggest that the franchise value is not only embedded in failed banks’ core deposits but also in the size of their branch networks. Moreover, bidders with more capital tend to pay lower prices for failed banks. Failed banks are sold at higher prices in more competitive auctions.
Keywords: Bank failures, Resolution, FDIC
JEL Classification: G21, G28
Using Iran’s unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietary information on more than 53,000 farmers, we find that farmers with a stronger relationship with their branch – particularly younger and females – are more likely to receive a recovery loan. Our findings underscore that despite recent technological advancements, relationship-based branch banking is still important for agrarian societies during catastrophic events.
Keywords: Bank branch, Relationship lending, Climate change, Agricultural loans
JEL Classification: G21, G28, O13, Q14, Q54
What is the role played by marketplace lending after natural disasters? Analyzing a sample of more than one and a half million observations from Lending Club around the 33 worst natural disasters that occurred between 2013 and 2017, we find that there is an increase in the demand for marketplace loans by almost 10%. Yet, the platform does not restrict lending to individuals in the affected areas, nor do we observe an increase in interest rates. Interestingly, the performance of borrowers who receive loans after a natural disaster is not significantly different from the borrowers during normal times, indicating that the platform is competent at efficiently meeting the extra loan demand.
Keywords: Marketplace Lending, FinTech, Natural Disasters, Access to Finance, Credit Risk Assessment
JEL Classification: D14, E51, G2, Q54
This paper primarily studies the pricing of insolvent banks that are sold under the purchase and assumption resolution method of the Federal Deposit Insurance Corporation (FDIC). We analyze 586 acquisitions of solvent and insolvent U.S. banks between 2009:Q1 and 2016:Q3 and find that acquirers pay higher prices for insolvent banks with more branches or with a national charter. Our findings hence suggest that the franchise value is not only embedded in failed banks’ core deposits but also in the size of their branch networks. Moreover, bidders with more capital tend to pay lower prices for failed banks. Failed banks are sold at higher prices in more competitive auctions.
Keywords: Bank failures, Resolution, FDIC
JEL Classification: G21, G28
Admission to the program is highly selective; there are many more qualified applicants than there are places in the program. One of the following qualifications is necessary for your application to be processed:
